9 citations · 17 across the 8 of their papers we have counts for
6 papers · 1 filter
Predictive Control with Learning-Based Terminal Costs Using Approximate Value Iteration
Francisco Moreno-Mora, Lukas Beckenbach, Stefan Streif
Stability under model predictive control (MPC) schemes is frequently ensured by terminal ingredients. Employing a (control) Lyapunov function as the terminal cost constitutes a com…
A stabilizing reinforcement learning approach for sampled systems with partially unknown models
Lukas Beckenbach, Pavel Osinenko, Stefan Streif
Reinforcement learning is commonly associated with training of reward-maximizing (or cost-minimizing) agents, in other words, controllers. It can be applied in model-free or model-…
Approximate infinite-horizon predictive control
Lukas Beckenbach, Stefan Streif
Predictive control is frequently used for control problems involving constraints. Being an optimization based technique utilizing a user specified so-called stage cost, performance…
Performance bounds of adaptive MPC with bounded parameter uncertainties
Francisco Moreno-Mora, Lukas Beckenbach, Stefan Streif
Model predictive control is a control approach that minimizes a stage cost over a predicted system trajectory based on a model of the system and is capable of handling state and in…
On performance bound estimation in NMPC with time-varying terminal cost
Lukas Beckenbach, Stefan Streif
Model predictive control (MPC) schemes are commonly designed with fixed, i.e., time-invariant, horizon length and cost functions. If no stabilizing terminal ingredients are used, s…
Model Predictive Control of a Food Production Unit: A Case Study for Lettuce Production
Murali Padmanabha, Lukas Beckenbach, Stefan Streif
Plant factories with artificial light are widely researched for food production in a controlled environment. For such control tasks, models of the energy and resource exchange in t…